AI Fraud Prevention

Detect Fraud Patterns That Human Eyes Can’t

Uncover complex fraud patterns and continuously improve your fraud detection with proven AI-insights from whitebox and blackbox machine learning models.

Scale AI to detect suspicious patterns in vast datasets
Use machine learning that adapts to evolving fraud trends
Reduce fraud with real-time, AI-powered decisions

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Trusted by the World’s Most Ambitious Companies

UNDERSTAND RISK FASTER

Turn Raw Signals Into Clear Context

Get Started in Days, Not Months

Start detecting risk from day one with high-performing AI insights powered by 900+ first-party fraud signals
Combine AI insights with rules-based decisioning to catch known and emerging threats
See exactly which signals influenced the AI insights score to understand choices and accelerate confident reviews

Read about the AI insights score

Catch Emerging Threats With AI Rule Suggestions

Identify new risk patterns as they emerge with continuously updated AI models
Receive proactive AI rule suggestions tailored to evolving fraud and AML tactics
See how each suggested rule would perform, including the expected accuracy and transaction impact

Spot threats faster with AI rules suggestions

Get Immediate Insight Into Risky Signals

Spend less time digging for information and more time taking informed action
Distill complex data and decisioning with AI summaries for alerts and transactions
Quickly spot high, medium and low risk factors at a glance to clearly guide investigations
Reduce analyst misinterpretation with consistent, easy-to-understand AI summaries that explain core signals and suggest next steps

Explore AI summaries

Train Models On Real-World Results

Strengthen detection logic with every verified decision
Apply preset labeled outcomes, like synthetic identity or bonus abuse, to make models smarter, more accurate and better adept at spotting evolving risks
Ensure consistent labeling across teams to improve model learning and reduce bias in future decisions

Learn how to label transactions

Automate Your Next Move

Eliminate repetitive manual tasks so your team can focus on high-value work
Ensure faster, more consistent follow-ups after every fraud or AML decision to maintain clean audit trails
Instantly trigger actions like tagging users, assigning labels or updating statuses

Setup post-decision automations

Discover How Companies Win

“I couldn’t believe how fast the results came. Our chargeback rates dropped by 91% in one month. Moreover, the number of fraud catch rates continued to improve in the following 6 months, which is the benefit of deploying a machine learning algorithm to fine-tune accuracy.”

Gergely Kalman

CEO at Unbuffered

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“We saw an immediate 25% drop in fraudulent transactions and when we layered on machine learning, we increased the accuracy of detecting fraud by an additional 15%.”

Lucrecia Vera

Partner, Solventa

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See all customer stories

Learn More About Machine Learning & AI

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Fraud Detection with Machine Learning & AI

Learn how AI and machine learning detect and prevent fraud in real time across industries.
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Blackbox Machine Learning

Blackbox machine learning detects complex fraud patterns but lacks transparency, making it best paired with explainable tools like SEON.
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Whitebox Machine Learning

Whitebox machine learning enhances fraud prevention with transparent decisions, customizable rules, and improved detection.

Frequently Asked Questions

Can I customize AML rules based on my internal policies?

Yes. SEON lets you tailor every alert trigger and rule to your internal risk appetite, compliance policies and regional obligations all without writing code. You can adjust rule thresholds, select which data signals to use, and define conditions based on fraud, AML, or behavioral insights to fit your evolving needs. You can read more about rule recommendations and AML transaction monitoring here.

Does SEON support real-time transaction monitoring?

Absolutely. SEON surfaces suspicious activity by analyzing transactions in real time using behavioral patterns, customer context and AML signals. This helps teams move beyond batch reviews and take immediate action when needed.

How does SEON help reduce false positives in AML alerts?

SEON reduces alert fatigue by letting you set highly specific, granular rules and alert triggers for every scenario imaginable that focus on true risk, not noise. By layering fraud signals (like IPs and devices) with AML and transactional data, analysts can better prioritize alerts and avoid wasting time on low-risk activity.

Is it possible to file SARs or other regulatory reports directly from SEON?

Yes. SEON supports direct filing of SAR, CTR and Form 8300 reports to FinCEN. Reports are pre-filled from case data and include audit trails and submission status, saving time and reducing the risk of manual errors.

How do I set AML transaction thresholds in SEON?

You can define transaction thresholds using SEON’s no-code rule and alert trigger builder. Rules and alert triggers can be set by amount, frequency, velocity and even behavioral triggers. Adjust thresholds per user segment, jurisdiction, product or business scenario to stay aligned with your internal controls and regulatory requirements.